Masami Okada

Initial results from WING, the continuous GPS network in the western Pacific area

To investigate tectonic deformation in the western Pacific, a continuous GPS tracking network has been established, and named the Western Pacific Integrated Network of GPS (WING). Between 1995 and March 1997 we establised ten new sites. Data for the period July 1995 to October 1996 were analyzed, together with data from International GPS Service for Geodynamics (IGS) global sites, to estimate daily coordinates. A fiducial-free approach was used to obtain the most accurate baseline estimates. To fix the estimated coordinates to the terrestrial reference frame, the Tsukuba IGS site is assumed to be moving westward relative to the stable Eurasian continent at ∼2 cm/yr according to Hekis [1996] estimate. We find that: (1) velocities of sites well within oceanic plates are in good agreement with rigid plate motion models; (2) sites close to plate boundaries are all affected by the deformation at those boundaries, among which back-arc rifting (spreading) is clearly visible at the Mariana and Okinawa troughs; (3) sites in eastern Asia are moving east to east-southeast relative to the stable Eurasian continent, suggesting long distance effects of the northward collision of India with Asia.

Source Model of Noto-Hanto-Oki Earthquake Tsunami of 7 February 1993

A source model was discussed for a small tsunami accompanied by the Noto-Hanto-Oki earthquake (Ms 6.6), striking Japan on 7 February, 1994. Assuming a fault model under the sea bottom, we estimated the focal parameters jointly, using synthesized tsunami source spectra as well as the tsunami numerical simulation. The fault proposed by this study consists of a plane sized 15×15 km, dipping N47°W with the dip angle of 42°, which is almost pure reverse fault (slip angle 87°) with a dislocation of 1 meter. The numerical simulation shows that the shallow sea in the source region caused a comparatively long recurring tsunami (the periods are 12–18 minutes) in spite of its small size. The model fault is corresponding to an aftershock area of this earthquake.

Probabilistic Estimation of Large Earthquake Occurrence from Several Earthquakes Using Lognormal Distribution Model: Re-evaluation for the Oncoming Earthquake off Miyagi Prefecture, Japan@@@宮城県沖地震の再検討

I statistically discuss the method for estimating the probability of the next characteristic earthquake in a given time interval from the data on date of earthquakes in the past by using lognormal distribution model, based on the Bayesian approach. We assume that n + 1 earthquakes have occurred on a fault or in a source area separated by n time intervals, Tti, of which logarithm, xi= ln(Ti), are considered to follow a normal distribution, N(ƒÊ, ƒÂ2). Here, t and a2 are mean and variance parameters of a normal population distribution, respectively. Then the likelihood accounted for aseismic period since the last event is defined as L(ƒÊ, ƒÂ2) = (1-FN(xp; ,ƒÊ ƒÂ2)) I n-1 fN(xi; ƒÊ, ƒÂ2), where xp, FN and fN are the logarithm of the time interval of aseismic period, Tp, since the last event, the cumulative distribution function, and the probability density function for N(ƒÊ, ƒÂ2), respectively. We expect that normalized likelihood represents the density distribution of ƒÊ, ƒÂ2 based on Bayesian rule with a prior distribution of ir(ƒÊ, ƒÂ2)= 1. If , ƒÊ and ƒÂ2 are known, the probability of the next earthquake occurring in the forthcoming period from Tp through Tp+‡TMT is denoted by a conditional probability, Pq=(FN(xf;,ƒÊ, .A2)-FN(xp; ƒÊ , ƒÂ2))/(1-FN(xp; ƒÊ, ƒÂ2)), where xf=ln(Tp+‡TMT). However it is impossible to estimate real values from a small number of data without large error, and we can only know the distribution of parameters to calculate numerically the distribution of Pq as shown in this paper. The distribution of expected time interval, T, from the last event to the next event is computed analytically from a law that •ãn-3 (ln(T)-x)/ •ã(n+ 1)s2 follows t-distribution of n-3 degrees of freedom. Here x and s2 are mean and variance of data, xi=ln(Ti). And the expected probability of characteristic earthquake occurrence in a time interval ‡TMT given that no earthquake has occurred in Tp, is the mean of variable Pq or a conditional probability of t-distribution. For the characteristic earthquakes off Miyagi prefecture, Japan, the estimates of probability in the periods of 10, 20 and 30 years after January 2001 are 0.28, 0.62 and 0.80, respectively, using the data set compiled by the Earthquake Research Committee of Japan. These estimates for 20 and 30 years are smaller than those, about 0.8 and larger than 0.9, given by the committee, respectively. Interval estimates of Pq for those periods are 0.15-0.41, 0.42-0.82 and 0.75-1.0.